Weighted ensemble networks for multiview based tiny object quality assessment-Reference-Cited by-同舟云学术

Weighted ensemble networks for multiview based tiny object quality assessment

Published:2021-01-23 Issue:6 Volume:33 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Zhou Yichao¹,Wu Wanyin²³,Zou Jie¹,Qiao Jianwang¹,Cheng Jun⁴⁵^ORCID

Affiliation:

1. State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment China Nuclear Power Design Company Ltd. Shenzhen China

2. United Vision Innovations Science and Technology Ltd. Shenzhen China

3. Yunnan United Vision Science and Technology Ltd. Yunnan China

4. CAS Key Laboratory of Human‐Machine Intelligence‐Synergy Systems Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen China

5. Chinese University of Hong Kong Hong Kong China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.5995

Reference53 articles.

1. Fully automatic model‐based segmentation and classification approach for MRI brain tumor using artificial neural networks

2. Random Drop Loss for Tiny Object Segmentation: Application to Lesion Segmentation in Fundus Images

3. A mobile vision inspection system for tiny defect detection on smooth car-body surfaces based on deep ensemble learning

4. Machine vision system for food grain quality evaluation: A review

5. Quantitative Determination of Rice Moisture Based on Hyperspectral Imaging Technology and BCC-LS-SVR Algorithm

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Temporal-Quality Ensemble Technique for Handling Image Blur in Packaging Defect Inspection;Sensors;2024-07-09

2. A weight recognition method for movable objects in sealed cavity based on supervised learning;Measurement;2022-12

3. A Weight Recognition Method for Movable Objects in Sealed Cavity Based on Supervised Learning;SSRN Electronic Journal;2022

4. Weighted ensemble networks for multiview based tiny object quality assessment;Concurrency and Computation: Practice and Experience;2021-01-23